Triple
T920285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oregon Trail |
E19866
|
entity |
| Predicate | estimatedNumberOfEmigrants |
P17800
|
FINISHED |
| Object | over 300,000 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: over 300,000 | Statement: [Oregon Trail, estimatedNumberOfEmigrants, over 300,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedNumberOfEmigrants Context triple: [Oregon Trail, estimatedNumberOfEmigrants, over 300,000]
-
A.
estimatedEmigrants
chosen
Indicates the estimated number of people who have left a place or country to live elsewhere.
-
B.
numberOfImmigrantsProcessed
Indicates the total count of immigrants that have been processed in a given context or system.
-
C.
estimatedNumberEmancipated
Indicates the estimated count of individuals who have been emancipated.
-
D.
yearOfEmigration
Indicates the specific year in which an entity permanently left its country or place of origin to settle elsewhere.
-
E.
immigratedTo
Indicates that an entity moved from its country of origin to live permanently in another specified country or region.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a493a099788190a696d9d8408cbaf4 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b388f0bc8190a087222636135ba5 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b2944ff88190a260be5355132ba5 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.